{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import copy\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import networkx as nx\n",
    "import numpy as np\n",
    "import numpy.random as rnd\n",
    "import tsplib95\n",
    "import tsplib95.distances as distances\n",
    "\n",
    "from alns import ALNS\n",
    "from alns.accept import HillClimbing\n",
    "from alns.select import RouletteWheel\n",
    "from alns.stop import MaxRuntime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "SEED = 7654"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# The travelling salesman problem\n",
    "\n",
    "The travelling salesman problem (TSP) is a classic problem in operations research. It asks how to construct the minimum distance tour between a number of nodes, such that each node is visited once and the tour concludes at the starting city (that is, it forms a cycle). It is perhaps the best-known problem in the class of [NP-hard](https://en.wikipedia.org/wiki/NP-hardness) problems.\n",
    "\n",
    "## Data\n",
    "There are a considerable number of test data sets available for the TSP, varying in size from a hundred or so locations to many hundreds of thousands. For the sake of exposition, we shall use one of the smaller data sets: the data from the XQF131 VLSI instance, made available [here](http://www.math.uwaterloo.ca/tsp/vlsi/index.html#XQF131). It consists of 'only' 131 nodes, with an optimal tour length of 564."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total optimal tour length is 564.\n"
     ]
    }
   ],
   "source": [
    "DATA = tsplib95.load('data/xqf131.tsp')\n",
    "CITIES = list(DATA.node_coords.keys())\n",
    "\n",
    "# Precompute the distance matrix - this saves a bunch of time evaluating moves.\n",
    "# + 1 since the cities start from one (not zero).\n",
    "COORDS = DATA.node_coords.values()\n",
    "DIST = np.empty((len(COORDS) + 1, len(COORDS) + 1))\n",
    "\n",
    "for row, coord1 in enumerate(COORDS, 1):\n",
    "    for col, coord2 in enumerate(COORDS, 1):\n",
    "        DIST[row, col] = distances.euclidean(coord1, coord2)\n",
    "\n",
    "SOLUTION = tsplib95.load('data/xqf131.opt.tour')\n",
    "OPTIMAL = DATA.trace_tours(SOLUTION.tours)[0]\n",
    "\n",
    "print(f\"Total optimal tour length is {OPTIMAL}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def draw_graph(graph, only_nodes=False):\n",
    "    \"\"\"\n",
    "    Helper method for drawing TSP (tour) graphs.\n",
    "    \"\"\"\n",
    "    fig, ax = plt.subplots(figsize=(12, 6))\n",
    "\n",
    "    if only_nodes:\n",
    "        nx.draw_networkx_nodes(graph, DATA.node_coords, node_size=25, ax=ax)\n",
    "    else:\n",
    "        nx.draw_networkx(graph, DATA.node_coords, node_size=25, with_labels=False, ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_graph(DATA.get_graph(), only_nodes=True)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To use the ALNS meta-heuristic, we need to have destroy and repair operators that work on a proposed solution, and a way to describe such a solution in the first place.\n",
    "Let's start with the solution state."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Solution state"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "class TspState:\n",
    "    \"\"\"\n",
    "    Solution class for the TSP problem. It has two data members, nodes, and edges.\n",
    "    nodes is a list of IDs. The edges data member, then, is a mapping from each node\n",
    "    to their only outgoing node.\n",
    "    \"\"\"\n",
    "\n",
    "    def __init__(self, nodes, edges):\n",
    "        self.nodes = nodes\n",
    "        self.edges = edges\n",
    "        \n",
    "    def objective(self):\n",
    "        \"\"\"\n",
    "        The objective function is simply the sum of all individual edge lengths,\n",
    "        using the rounded Euclidean norm.\n",
    "        \"\"\"\n",
    "        return sum(DIST[node, self.edges[node]] for node in self.nodes)\n",
    "\n",
    "    def to_graph(self):\n",
    "        \"\"\"\n",
    "        NetworkX helper method.\n",
    "        \"\"\"\n",
    "        graph = nx.Graph()\n",
    "\n",
    "        for node in self.nodes:\n",
    "            graph.add_node(node, pos=DATA.node_coords[node])\n",
    "\n",
    "        for node_from, node_to in self.edges.items():\n",
    "            graph.add_edge(node_from, node_to)\n",
    "\n",
    "        return graph"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Destroy operators\n",
    "\n",
    "Destroy operators break parts of a solution down, leaving an incomplete state. This is the first part of each iteration of the ALNS meta-heuristic; the incomplete solution is subsequently repaired by any one repair operator. We will consider three destroy operators: **worst removal**, **path removal** and **random removal**. We will also use a separate parameter, the degree of destruction, to control the extent of the damage done to a solution in each step."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "DEGREE_OF_DESTRUCTION = 0.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def edges_to_remove(state):\n",
    "    return int(len(state.edges) * DEGREE_OF_DESTRUCTION)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def worst_removal(current, rnd_state):\n",
    "    \"\"\"\n",
    "    Worst removal iteratively removes the 'worst' edges, that is,\n",
    "    those edges that have the largest distance.\n",
    "    \"\"\"\n",
    "    destroyed = copy.deepcopy(current)\n",
    "\n",
    "    worst_edges = sorted(destroyed.nodes,\n",
    "                         key=lambda node: DIST[node, destroyed.edges[node]])\n",
    "\n",
    "    for idx in range(edges_to_remove(current)):\n",
    "        del destroyed.edges[worst_edges[-(idx + 1)]]\n",
    "\n",
    "    return destroyed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def path_removal(current, rnd_state):\n",
    "    \"\"\"\n",
    "    Removes an entire consecutive sub-path, that is, a series of\n",
    "    contiguous edges.\n",
    "    \"\"\"\n",
    "    destroyed = copy.deepcopy(current)\n",
    "    \n",
    "    node_idx = rnd_state.choice(len(destroyed.nodes))\n",
    "    node = destroyed.nodes[node_idx]\n",
    "    \n",
    "    for _ in range(edges_to_remove(current)):\n",
    "        node = destroyed.edges.pop(node)\n",
    "\n",
    "    return destroyed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def random_removal(current, rnd_state):\n",
    "    \"\"\"\n",
    "    Random removal iteratively removes random edges.\n",
    "    \"\"\"\n",
    "    destroyed = copy.deepcopy(current)\n",
    "    \n",
    "    for idx in rnd_state.choice(len(destroyed.nodes),\n",
    "                                edges_to_remove(current),\n",
    "                                replace=False):\n",
    "        del destroyed.edges[destroyed.nodes[idx]]\n",
    "\n",
    "    return destroyed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Repair operators\n",
    "\n",
    "We implement a simple, **greedy repair** strategy. It determines a set of nodes that are currently not visited, and then links these up to the tour such that it forms one cycle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def would_form_subcycle(from_node, to_node, state):\n",
    "    \"\"\"\n",
    "    Ensures the proposed solution would not result in a cycle smaller\n",
    "    than the entire set of nodes. Notice the offsets: we do not count\n",
    "    the current node under consideration, as it cannot yet be part of\n",
    "    a cycle.\n",
    "    \"\"\"\n",
    "    for step in range(1, len(state.nodes)):\n",
    "        if to_node not in state.edges:\n",
    "            return False\n",
    "\n",
    "        to_node = state.edges[to_node]\n",
    "        \n",
    "        if from_node == to_node and step != len(state.nodes) - 1:\n",
    "            return True\n",
    "\n",
    "    return False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def greedy_repair(current, rnd_state):\n",
    "    \"\"\"\n",
    "    Greedily repairs a tour, stitching up nodes that are not departed\n",
    "    with those not visited.\n",
    "    \"\"\"\n",
    "    visited = set(current.edges.values())\n",
    "  \n",
    "    # This kind of randomness ensures we do not cycle between the same\n",
    "    # destroy and repair steps every time.\n",
    "    shuffled_idcs = rnd_state.permutation(len(current.nodes))\n",
    "    nodes = [current.nodes[idx] for idx in shuffled_idcs]\n",
    "\n",
    "    while len(current.edges) != len(current.nodes):\n",
    "        node = next(node for node in nodes \n",
    "                    if node not in current.edges)\n",
    "\n",
    "        # Computes all nodes that have not currently been visited,\n",
    "        # that is, those that this node might visit. This should\n",
    "        # not result in a subcycle, as that would violate the TSP\n",
    "        # constraints.\n",
    "        unvisited = {other for other in current.nodes\n",
    "                     if other != node\n",
    "                     if other not in visited\n",
    "                     if not would_form_subcycle(node, other, current)}\n",
    "\n",
    "        # Closest visitable node.\n",
    "        nearest = min(unvisited,\n",
    "                      key=lambda other: DIST[node, other])\n",
    "\n",
    "        current.edges[node] = nearest\n",
    "        visited.add(nearest)\n",
    "\n",
    "    return current"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initial solution\n",
    "\n",
    "We start from a very simple, greedily constructed initial solution. This solution is not good (as can clearly be seen below), but it is feasible."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initial solution objective is 870.0.\n"
     ]
    }
   ],
   "source": [
    "random_state = rnd.RandomState(SEED)\n",
    "state = TspState(CITIES, {})\n",
    "    \n",
    "init_sol = greedy_repair(state, random_state)\n",
    "print(f\"Initial solution objective is {init_sol.objective()}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_graph(init_sol.to_graph())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Heuristic solution\n",
    "\n",
    "Here we perform the ALNS procedure. The heuristic is given 60 seconds of runtime."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "alns = ALNS(random_state)\n",
    "\n",
    "alns.add_destroy_operator(random_removal)\n",
    "alns.add_destroy_operator(path_removal)\n",
    "alns.add_destroy_operator(worst_removal)\n",
    "\n",
    "alns.add_repair_operator(greedy_repair)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "select = RouletteWheel([3, 2, 1, 0.5], 0.8, 3, 1)\n",
    "accept = HillClimbing()\n",
    "stop = MaxRuntime(60)\n",
    "\n",
    "result = alns.iterate(init_sol, select, accept, stop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best heuristic objective is 576.0.\n",
      "This is 2.1% worse than the optimal solution, which is 564.\n"
     ]
    }
   ],
   "source": [
    "solution = result.best_state\n",
    "objective = solution.objective()\n",
    "pct_diff = 100 * (objective - OPTIMAL) / OPTIMAL\n",
    "\n",
    "print(f\"Best heuristic objective is {objective}.\")\n",
    "print(f\"This is {pct_diff:.1f}% worse than the optimal solution, which is {OPTIMAL}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, ax = plt.subplots(figsize=(12, 6))\n",
    "result.plot_objectives(ax=ax, lw=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's have a look at the solution:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_graph(solution.to_graph())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusions\n",
    "\n",
    "In the code above we implemented a very simple heuristic for the TSP, using the ALNS meta-heuristic framework. We did not tinker too much with the various hyperparameters available on the ALNS implementation, but even for these relatively basic heuristic methods and workflow we find a very good result - just 2% worse than the optimal tour.\n",
    "\n",
    "This notebook showcases how the ALNS library may be put to use to construct powerful, efficient heuristic pipelines from simple, locally greedy operators."
   ]
  }
 ],
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